Subodh Pushkar
MLOps - ML Monitoring And Observability at Mercari, Inc.
Tokyo, Japan
Summary
👤
Senior🎓
Top SchoolSubodh Pushkar is an MLOps and ML Infrastructure engineer based in Tokyo with 9 years of experience and a 6+ year focus on building scalable ML systems, observability, and deployment pipelines. At Mercari he designed MonitorX using Evidently AI for unified model monitoring, integrated Triton logging for online observability, and led Kubeflow upgrades that cut storage costs by $65K/year while enabling multi-tenancy. He has a strong track record of improving inference performance and reliability—migrating core services to GCP with autoscaling to boost throughput by 30%—and has productionized high-accuracy models with optimized Kubernetes training/serving pipelines. Trained in Math and Computer Science at IIT Delhi, he blends deep ML platform engineering with pragmatic cost and security improvements, often focusing on cross-team automation and lifecycle data management that aren’t obvious from model metrics alone.
9 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Github Skills (63)
notebook10
jupyter10
deploying9
google-kubernetes-engine9
tekton9
kubernetes9
machine-learning9
kubeflow9
pipeline9
kedro9
kubeflow-pipelines9
minikube9
github-token9
python8
mlops8
Programming languages (7)
Github contributions (5)
subodh101/glucoma_segmentation
Aug 2018 - Oct 2018
Contributions:15 commits, 13 pushes, 1 branch in 2 months
subodh101/my-zsh-setup
Feb 2020 - Apr 2021
Contributions:7 commits, 6 pushes, 1 branch in 1 year 2 months
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